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Software Probes: Towards a Quick Method for Machine Characterization and Application Performance Prediction

机译:软件探针:迈向机器表征和应用性能预测的快速方法

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Computers perform different applications in different ways. To characterize an application performance into a machine, the usual method is a throughout execution of it. This work is a step into a synthetic probe able to characterize a master-worker application's performance in a fraction of the time required to run it entirely. This is specially important for CPU-intensive scientific applications, who runs for very long, as it makes sense that it runs as efficiently (and fast) as possible. To know how, and for how long a master-worker application is going to run can guide the decision to use this machine or not. Our software probe takes into account only the performance-relevant parts of the application, discovering a program's relevant phases. Running solely these significant phases is a powerful way to quickly characterize the application's performance on a machine. It can help to select the best computing nodes in a grid or in a multi-cluster to run this application, and even quickly predict the total execution time for this application/data set in the machine analyzed. We also present ongoing work on a fully synthetic probe generated from programs' phases.
机译:计算机以不同方式执行不同的应用程序。要在计算机中表征应用程序性能,通常的方法是整个执行。这项工作是一个综合探测的步骤,能够在一小部分运行它的一小部分中表征主工作人员应用程序的性能。这对CPU密集型科学应用特别重要,他们持续很长时间,因为它有意义,它可以尽可能有效地运行(和快速)。要了解如何,以及乘员申请将要运行多长时间才能指导决定使用此机器。我们的软件探测只考虑了应用程序的性能相关部分,发现程序的相关阶段。仅仅跑步这些重要阶段是一种快速表征应用程序在机器上的性能的强大方法。它可以帮助选择网格中的最佳计算节点或在多集群中运行此应用程序,甚至可以快速预测分析机器中的此应用程序/数据集的总执行时间。我们还在从程序阶段产生的完全合成探针上呈现持续的工作。

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